How can I optimize energy use in multi-mode robot task allocation?
Energy-Aware Task Allocation for Teams of Multi-mode Robots
This paper introduces a new way to assign tasks to a team of robots that can switch between different modes (like flying, driving, or walking). It aims to optimize task completion while minimizing energy consumption, considering each mode's capabilities and energy efficiency. The system uses an optimization algorithm and a constraint-based method to ensure robots select the best mode for a given task and avoid conflicts.
Relevant to LLM-based multi-agent systems, the paper demonstrates: * A formal model for representing agent capabilities and modes, translatable to LLM agent prompts and contexts. * A prioritization scheme for task allocation and mode switching that can be adapted to LLM agents based on prompt complexity, context length, or inference cost. * A method for handling constraints and optimizing for multiple objectives, applicable to LLM-based agents with diverse capabilities and resource limitations. * A theoretical framework for analyzing system stability and convergence, potentially adaptable for evaluating the behavior of multi-agent LLM systems.